Systems I Introduction to Computer Systems Don Fussell Spring 2011 Topics Theme Five great realities of computer systems How this fits within CS curriculum University of Texas at Austin CS429H Introduction to Computer Systems Fall 2011 Don Fussell Course Theme Abstraction is good but don t forget reality Courses to date emphasize abstraction Abstract data types Asymptotic analysis These abstractions have limits Especially in the presence of bugs Need to understand underlying implementations Useful outcomes Become more effective programmers Able to find and eliminate bugs efficiently Able to tune program performance Prepare for later systems classes in CS Compilers Operating Systems Networks Computer Architecture etc University of Texas at Austin CS429H Introduction to Computer Systems Fall 2011 Don Fussell 2 Great Reality 1 Int s are not Integers Float s are not Reals Examples Is x2 0 Float s Yes Int s 40000 40000 1600000000 50000 50000 Is x y z x y z Unsigned Signed Int s Float s Yes 1e20 1e20 3 14 3 14 1e20 1e20 3 14 University of Texas at Austin CS429H Introduction to Computer Systems Fall 2011 Don Fussell 3 Computer Arithmetic Does not generate random values Arithmetic operations have important mathematical properties Cannot assume usual properties Due to finiteness of representations Integer operations satisfy ring properties Commutativity associativity distributivity Floating point operations satisfy ordering properties Monotonicity values of signs Observation Need to understand which abstractions apply in which contexts Important issues for compiler writers and serious application programmers University of Texas at Austin CS429H Introduction to Computer Systems Fall 2011 Don Fussell 4 Great Reality 2 You ve got to know assembly Chances are you ll never write program in assembly Compilers are much better more patient than you are Understanding assembly key to machine level execution model Behavior of programs in presence of bugs High level language model breaks down Tuning program performance Understanding sources of program inefficiency Implementing system software Compiler has machine code as target Operating systems must manage process state University of Texas at Austin CS429H Introduction to Computer Systems Fall 2011 Don Fussell 5 Assembly Code Example Time Stamp Counter Special 64 bit register in Intel compatible machines Incremented every clock cycle Read with rdtsc instruction Application Measure time required by procedure In units of clock cycles double t start counter P t get counter printf P required f clock cycles n t University of Texas at Austin CS429H Introduction to Computer Systems Fall 2011 Don Fussell 6 Code to Read Counter Write small amount of assembly code using GCC s asm facility Inserts assembly code into machine code generated by compiler static unsigned cyc hi 0 static unsigned cyc lo 0 Set hi and lo to the high and low order bits of the cycle counter void access counter unsigned hi unsigned lo asm rdtsc movl edx 0 movl eax 1 r hi r lo edx eax University of Texas at Austin CS429H Introduction to Computer Systems Fall 2011 Don Fussell 7 Code to Read Counter Record the current value of the cycle counter void start counter access counter cyc hi cyc lo Number of cycles since the last call to start counter double get counter unsigned ncyc hi ncyc lo unsigned hi lo borrow Get cycle counter access counter ncyc hi ncyc lo Do double precision subtraction lo ncyc lo cyc lo borrow lo ncyc lo hi ncyc hi cyc hi borrow return double hi 1 30 4 lo University of Texas at Austin CS429H Introduction to Computer Systems Fall 2011 Don Fussell 8 Measuring Time Trickier than it Might Look Many sources of variation Example Sum integers from 1 to n n 100 1 000 1 000 10 000 10 000 1 000 000 1 000 000 1 000 000 000 University of Texas at Austin Cycles 961 8 407 8 426 82 861 82 876 8 419 907 8 425 181 8 371 2305 591 Cycles n 9 61 8 41 8 43 8 29 8 29 8 42 8 43 8 37 CS429H Introduction to Computer Systems Fall 2011 Don Fussell 9 Great Reality 3 Memory Matters Memory is not unbounded It must be allocated and managed Many applications are memory dominated Memory referencing bugs especially pernicious Effects are distant in both time and space Memory performance is not uniform Cache and virtual memory effects can greatly affect program performance Adapting program to characteristics of memory system can lead to major speed improvements University of Texas at Austin CS429H Introduction to Computer Systems Fall 2011 Don Fussell 10 Memory Referencing Bug Example main long int a 2 double d 3 14 a 2 1073741824 Out of bounds reference printf d 15g n d exit 0 Alpha MIPS Linux g 5 30498947741318e 315 3 1399998664856 3 14 O 3 14 3 14 3 14 Linux version gives correct result but implementing as separate function gives segmentation fault University of Texas at Austin CS429H Introduction to Computer Systems Fall 2011 Don Fussell 11 Memory Referencing Errors C and C do not provide any memory protection Out of bounds array references Invalid pointer values Abuses of malloc free Can lead to nasty bugs Whether or not bug has any effect depends on system and compiler Action at a distance Corrupted object logically unrelated to one being accessed Effect of bug may be first observed long after it is generated How can I deal with this Program in Java Lisp or ML Understand what possible interactions may occur Use or develop tools to detect referencing errors University of Texas at Austin CS429H Introduction to Computer Systems Fall 2011 Don Fussell 12 Memory Performance Example Implementations of Matrix Multiplication Multiple ways to nest loops ijk for i 0 i n i for j 0 j n j sum 0 0 for k 0 k n k sum a i k b k j c i j sum University of Texas at Austin jik for j 0 j n j for i 0 i n i sum 0 0 for k 0 k n k sum a i k b k j c i j sum CS429H Introduction to Computer Systems Fall 2011 Don Fussell 13 Matmult Performance Alpha 21164 Too big for L1 Cache Too big for L2 Cache 160 140 120 ijk 100 ikj jik 80 jki kij 60 kji 40 20 0 matrix size n University of Texas at Austin CS429H Introduction to Computer Systems Fall 2011 Don Fussell 14 Blocked matmult perf Alpha 21164 160 140 120 100 bijk bikj 80 ijk ikj 60 40 20 0 50 75 100 125 150 175 200 225 250 275 300 325 350 375 400 425 450 475 500 matrix size n University of Texas at Austin CS429H Introduction to Computer Systems Fall 2011 Don Fussell 15 Great Reality 4 There s more to performance than asymptotic complexity Constant factors matter too Easily see 10 1